Overview

Dataset statistics

Number of variables53
Number of observations8436087
Missing cells14486537
Missing cells (%)3.2%
Duplicate rows118
Duplicate rows (%)< 0.1%
Total size in memory3.4 GiB
Average record size in memory432.0 B

Variable types

Unsupported6
Numeric19
Categorical28

Alerts

Dataset has 118 (< 0.1%) duplicate rowsDuplicates
ghm2 has a high cardinality: 2071 distinct values High cardinality
anonyme has a high cardinality: 3579198 distinct values High cardinality
dp has a high cardinality: 11751 distinct values High cardinality
dr has a high cardinality: 7256 distinct values High cardinality
ghm_racine has a high cardinality: 614 distinct values High cardinality
departement has a high cardinality: 92 distinct values High cardinality
id_dep has a high cardinality: 92 distinct values High cardinality
Libellé GHM has a high cardinality: 2071 distinct values High cardinality
racine has a high cardinality: 614 distinct values High cardinality
Libellé GHM Racine has a high cardinality: 614 distinct values High cardinality
lib_dp has a high cardinality: 11749 distinct values High cardinality
top1_lib_dp_patients_None has a high cardinality: 731 distinct values High cardinality
top3_region_label_patients_None has a high cardinality: 199 distinct values High cardinality
top1_lib_dp_patients_SUV has a high cardinality: 991 distinct values High cardinality
top3_region_label_patients_SUV has a high cardinality: 640 distinct values High cardinality
top1_lib_dp_patients_CMU has a high cardinality: 743 distinct values High cardinality
top3_region_label_patients_CMU has a high cardinality: 251 distinct values High cardinality
top1_lib_dp_patients_AME has a high cardinality: 846 distinct values High cardinality
top3_region_label_patients_AME has a high cardinality: 260 distinct values High cardinality
annee is highly correlated with ano_dateHigh correlation
duree is highly correlated with costHigh correlation
ano_date is highly correlated with anneeHigh correlation
cost is highly correlated with dureeHigh correlation
annee is highly correlated with ano_dateHigh correlation
duree is highly correlated with costHigh correlation
supp_rea is highly correlated with nbActe and 1 other fieldsHigh correlation
ano_date is highly correlated with anneeHigh correlation
nbActe is highly correlated with supp_rea and 1 other fieldsHigh correlation
cost is highly correlated with duree and 2 other fieldsHigh correlation
duree is highly correlated with costHigh correlation
cost is highly correlated with dureeHigh correlation
departement is highly correlated with id_dep and 3 other fieldsHigh correlation
id_dep is highly correlated with departement and 3 other fieldsHigh correlation
region is highly correlated with departement and 3 other fieldsHigh correlation
label_cmd is highly correlated with hp_type and 1 other fieldsHigh correlation
severity is highly correlated with hp_typeHigh correlation
population_region is highly correlated with departement and 3 other fieldsHigh correlation
hp_type is highly correlated with label_cmd and 1 other fieldsHigh correlation
grp_cln is highly correlated with label_cmdHigh correlation
region_label is highly correlated with departement and 3 other fieldsHigh correlation
annee is highly correlated with ano_dateHigh correlation
age is highly correlated with label_cmdHigh correlation
duree is highly correlated with costHigh correlation
supp_rea is highly correlated with costHigh correlation
supp_si is highly correlated with supp_stfHigh correlation
supp_stf is highly correlated with supp_si and 1 other fieldsHigh correlation
supp_rep is highly correlated with costHigh correlation
ano_date is highly correlated with anneeHigh correlation
modeEntree is highly correlated with label_cmd and 1 other fieldsHigh correlation
motif is highly correlated with raison and 2 other fieldsHigh correlation
cost is highly correlated with duree and 3 other fieldsHigh correlation
raison is highly correlated with motif and 5 other fieldsHigh correlation
hp_type is highly correlated with severity and 3 other fieldsHigh correlation
severity is highly correlated with hp_type and 2 other fieldsHigh correlation
cmd is highly correlated with hp_type and 3 other fieldsHigh correlation
departement is highly correlated with motif and 6 other fieldsHigh correlation
id_dep is highly correlated with motif and 6 other fieldsHigh correlation
region_label is highly correlated with raison and 5 other fieldsHigh correlation
population_region is highly correlated with raison and 5 other fieldsHigh correlation
label_cmd is highly correlated with age and 5 other fieldsHigh correlation
region is highly correlated with raison and 5 other fieldsHigh correlation
effectif_region_2020 is highly correlated with departement and 4 other fieldsHigh correlation
grp_cln is highly correlated with modeEntree and 3 other fieldsHigh correlation
cmu has 632275 (7.5%) missing values Missing
motif has 7283520 (86.3%) missing values Missing
dr has 6570678 (77.9%) missing values Missing
supp_rea is highly skewed (γ1 = 56.47583919) Skewed
supp_si is highly skewed (γ1 = 256.8533838) Skewed
supp_stf is highly skewed (γ1 = 59.21071505) Skewed
supp_src is highly skewed (γ1 = 93.41008611) Skewed
supp_nn1 is highly skewed (γ1 = 39.37111543) Skewed
supp_nn2 is highly skewed (γ1 = 64.24186594) Skewed
supp_nn3 is highly skewed (γ1 = 95.89343888) Skewed
supp_rep is highly skewed (γ1 = 173.3399859) Skewed
nbActe is highly skewed (γ1 = 28.03181974) Skewed
finess is an unsupported type, check if it needs cleaning or further analysis Unsupported
sexe is an unsupported type, check if it needs cleaning or further analysis Unsupported
GHS is an unsupported type, check if it needs cleaning or further analysis Unsupported
modeSortie is an unsupported type, check if it needs cleaning or further analysis Unsupported
cmu is an unsupported type, check if it needs cleaning or further analysis Unsupported
top3_Libellé GHM_patients is an unsupported type, check if it needs cleaning or further analysis Unsupported
age has 463977 (5.5%) zeros Zeros
duree has 3417477 (40.5%) zeros Zeros
supp_rea has 8343918 (98.9%) zeros Zeros
supp_si has 8387701 (99.4%) zeros Zeros
supp_stf has 8233301 (97.6%) zeros Zeros
supp_src has 8275774 (98.1%) zeros Zeros
supp_nn1 has 8394806 (99.5%) zeros Zeros
supp_nn2 has 8418641 (99.8%) zeros Zeros
supp_nn3 has 8426871 (99.9%) zeros Zeros
supp_rep has 8421120 (99.8%) zeros Zeros
nbActe has 2113252 (25.1%) zeros Zeros

Reproduction

Analysis started2022-03-29 10:45:06.892268
Analysis finished2022-03-29 11:21:18.660790
Duration36 minutes and 11.77 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

finess
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size128.7 MiB

mois
Real number (ℝ≥0)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.467786902
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:18.752791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.434324781
Coefficient of variation (CV)0.5309891673
Kurtosis-1.216453641
Mean6.467786902
Median Absolute Deviation (MAD)3
Skewness-0.001480230321
Sum54562813
Variance11.7945867
MonotonicityNot monotonic
2022-03-29T13:21:18.841791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
10758554
9.0%
3741628
8.8%
6733999
8.7%
7726105
8.6%
9724177
8.6%
1714870
8.5%
11694109
8.2%
4687223
8.1%
5684782
8.1%
2684494
8.1%
Other values (2)1286146
15.2%
ValueCountFrequency (%)
1714870
8.5%
2684494
8.1%
3741628
8.8%
4687223
8.1%
5684782
8.1%
6733999
8.7%
7726105
8.6%
8644386
7.6%
9724177
8.6%
10758554
9.0%
ValueCountFrequency (%)
12641760
7.6%
11694109
8.2%
10758554
9.0%
9724177
8.6%
8644386
7.6%
7726105
8.6%
6733999
8.7%
5684782
8.1%
4687223
8.1%
3741628
8.8%

annee
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.1655
Minimum2012
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:18.940791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q12015
median2018
Q32020
95-th percentile2021
Maximum2021
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.862326397
Coefficient of variation (CV)0.00141898441
Kurtosis-1.139887454
Mean2017.1655
Median Absolute Deviation (MAD)2
Skewness-0.301236722
Sum1.701698365 × 1010
Variance8.192912401
MonotonicityNot monotonic
2022-03-29T13:21:19.024792image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
20211199595
14.2%
20201104689
13.1%
20191079405
12.8%
2018888920
10.5%
2017789612
9.4%
2016747399
8.9%
2015713405
8.5%
2014678502
8.0%
2013618513
7.3%
2012616047
7.3%
ValueCountFrequency (%)
2012616047
7.3%
2013618513
7.3%
2014678502
8.0%
2015713405
8.5%
2016747399
8.9%
2017789612
9.4%
2018888920
10.5%
20191079405
12.8%
20201104689
13.1%
20211199595
14.2%
ValueCountFrequency (%)
20211199595
14.2%
20201104689
13.1%
20191079405
12.8%
2018888920
10.5%
2017789612
9.4%
2016747399
8.9%
2015713405
8.5%
2014678502
8.0%
2013618513
7.3%
2012616047
7.3%

sexe
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size128.7 MiB

ghm2
Categorical

HIGH CARDINALITY

Distinct2071
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
28Z04Z
 
472898
28Z07Z
 
346199
28Z17Z
 
195174
20Z051
 
178104
14Z14A
 
155348
Other values (2066)
7088364 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05M13T
2nd row05M13T
3rd row05M13T
4th row05M13T
5th row05M13T

Common Values

ValueCountFrequency (%)
28Z04Z472898
 
5.6%
28Z07Z346199
 
4.1%
28Z17Z195174
 
2.3%
20Z051178104
 
2.1%
14Z14A155348
 
1.8%
14Z08Z121855
 
1.4%
28Z18Z121361
 
1.4%
06K04J111020
 
1.3%
23M20T88700
 
1.1%
15M05A77604
 
0.9%
Other values (2061)6567824
77.9%

Length

2022-03-29T13:21:19.121791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
28z04z472898
 
5.6%
28z07z346199
 
4.1%
28z17z195174
 
2.3%
20z051178104
 
2.1%
14z14a155348
 
1.8%
14z08z121855
 
1.4%
28z18z121361
 
1.4%
06k04j111020
 
1.3%
23m20t88700
 
1.1%
15m05a77604
 
0.9%
Other values (2061)6567824
77.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

GHS
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size128.7 MiB

age
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct121
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.53221843
Minimum0
Maximum133
Zeros463977
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:19.217791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119
median37
Q354
95-th percentile71
Maximum133
Range133
Interquartile range (IQR)35

Descriptive statistics

Standard deviation22.18349634
Coefficient of variation (CV)0.607231022
Kurtosis-0.8259814335
Mean36.53221843
Median Absolute Deviation (MAD)17
Skewness0.01157510785
Sum308188973
Variance492.1075097
MonotonicityNot monotonic
2022-03-29T13:21:19.332791image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0463977
 
5.5%
1184458
 
2.2%
2136821
 
1.6%
32134904
 
1.6%
30133530
 
1.6%
33133220
 
1.6%
31133140
 
1.6%
29132163
 
1.6%
53132092
 
1.6%
51131921
 
1.6%
Other values (111)6719861
79.7%
ValueCountFrequency (%)
0463977
5.5%
1184458
 
2.2%
2136821
 
1.6%
3123255
 
1.5%
4104929
 
1.2%
588216
 
1.0%
674645
 
0.9%
764734
 
0.8%
860666
 
0.7%
957057
 
0.7%
ValueCountFrequency (%)
1332
 
< 0.1%
1321
 
< 0.1%
1251
 
< 0.1%
1231
 
< 0.1%
1201
 
< 0.1%
1182
 
< 0.1%
1173
< 0.1%
1167
< 0.1%
1153
< 0.1%
1132
 
< 0.1%

duree
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct473
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.154064438
Minimum0
Maximum1645
Zeros3417477
Zeros (%)40.5%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:20.365739image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile13
Maximum1645
Range1645
Interquartile range (IQR)3

Descriptive statistics

Standard deviation7.729717129
Coefficient of variation (CV)2.4507163
Kurtosis1241.297192
Mean3.154064438
Median Absolute Deviation (MAD)1
Skewness17.57113827
Sum26607962
Variance59.7485269
MonotonicityNot monotonic
2022-03-29T13:21:20.473737image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
03417477
40.5%
11502202
17.8%
2805276
 
9.5%
3612202
 
7.3%
4492435
 
5.8%
5311205
 
3.7%
6229280
 
2.7%
7192810
 
2.3%
8136905
 
1.6%
998266
 
1.2%
Other values (463)638029
 
7.6%
ValueCountFrequency (%)
03417477
40.5%
11502202
17.8%
2805276
 
9.5%
3612202
 
7.3%
4492435
 
5.8%
5311205
 
3.7%
6229280
 
2.7%
7192810
 
2.3%
8136905
 
1.6%
998266
 
1.2%
ValueCountFrequency (%)
16451
< 0.1%
14781
< 0.1%
12461
< 0.1%
11921
< 0.1%
10211
< 0.1%
9381
< 0.1%
9221
< 0.1%
8431
< 0.1%
8351
< 0.1%
8311
< 0.1%

supp_rea
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct214
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1062228258
Minimum0
Maximum890
Zeros8343918
Zeros (%)98.9%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:20.598740image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum890
Range890
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.863669066
Coefficient of variation (CV)17.54490197
Kurtosis10366.36004
Mean0.1062228258
Median Absolute Deviation (MAD)0
Skewness56.47583919
Sum896105
Variance3.473262387
MonotonicityNot monotonic
2022-03-29T13:21:20.714738image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
08343918
98.9%
213438
 
0.2%
112566
 
0.1%
310283
 
0.1%
47849
 
0.1%
56180
 
0.1%
64994
 
0.1%
74251
 
0.1%
83296
 
< 0.1%
92781
 
< 0.1%
Other values (204)26531
 
0.3%
ValueCountFrequency (%)
08343918
98.9%
112566
 
0.1%
213438
 
0.2%
310283
 
0.1%
47849
 
0.1%
56180
 
0.1%
64994
 
0.1%
74251
 
0.1%
83296
 
< 0.1%
92781
 
< 0.1%
ValueCountFrequency (%)
8901
< 0.1%
5161
< 0.1%
4421
< 0.1%
4191
< 0.1%
3941
< 0.1%
3271
< 0.1%
3221
< 0.1%
2991
< 0.1%
2971
< 0.1%
2911
< 0.1%

supp_si
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct93
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01533092297
Minimum0
Maximum364
Zeros8387701
Zeros (%)99.4%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:20.848748image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum364
Range364
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4529428774
Coefficient of variation (CV)29.54439717
Kurtosis145985.7319
Mean0.01533092297
Median Absolute Deviation (MAD)0
Skewness256.8533838
Sum129333
Variance0.2051572501
MonotonicityNot monotonic
2022-03-29T13:21:20.949750image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
08387701
99.4%
124998
 
0.3%
29823
 
0.1%
34863
 
0.1%
42759
 
< 0.1%
51616
 
< 0.1%
61101
 
< 0.1%
7801
 
< 0.1%
8488
 
< 0.1%
9345
 
< 0.1%
Other values (83)1592
 
< 0.1%
ValueCountFrequency (%)
08387701
99.4%
124998
 
0.3%
29823
 
0.1%
34863
 
0.1%
42759
 
< 0.1%
51616
 
< 0.1%
61101
 
< 0.1%
7801
 
< 0.1%
8488
 
< 0.1%
9345
 
< 0.1%
ValueCountFrequency (%)
3641
< 0.1%
3621
< 0.1%
2701
< 0.1%
2281
< 0.1%
2081
< 0.1%
2011
< 0.1%
1961
< 0.1%
1611
< 0.1%
1561
< 0.1%
1411
< 0.1%

supp_stf
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct212
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1059596706
Minimum0
Maximum426
Zeros8233301
Zeros (%)97.6%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:21.066748image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum426
Range426
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.532512869
Coefficient of variation (CV)14.46317131
Kurtosis7322.375663
Mean0.1059596706
Median Absolute Deviation (MAD)0
Skewness59.21071505
Sum893885
Variance2.348595692
MonotonicityNot monotonic
2022-03-29T13:21:21.165747image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
08233301
97.6%
172269
 
0.9%
240256
 
0.5%
327002
 
0.3%
416918
 
0.2%
510787
 
0.1%
67164
 
0.1%
75244
 
0.1%
83548
 
< 0.1%
92502
 
< 0.1%
Other values (202)17096
 
0.2%
ValueCountFrequency (%)
08233301
97.6%
172269
 
0.9%
240256
 
0.5%
327002
 
0.3%
416918
 
0.2%
510787
 
0.1%
67164
 
0.1%
75244
 
0.1%
83548
 
< 0.1%
92502
 
< 0.1%
ValueCountFrequency (%)
4261
< 0.1%
4181
< 0.1%
4011
< 0.1%
3641
< 0.1%
3621
< 0.1%
3221
< 0.1%
3011
< 0.1%
2871
< 0.1%
2801
< 0.1%
2731
< 0.1%

supp_src
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct206
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08884510082
Minimum0
Maximum595
Zeros8275774
Zeros (%)98.1%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:21.277750image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum595
Range595
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.415456272
Coefficient of variation (CV)15.93173129
Kurtosis19232.33368
Mean0.08884510082
Median Absolute Deviation (MAD)0
Skewness93.41008611
Sum749505
Variance2.003516459
MonotonicityNot monotonic
2022-03-29T13:21:21.383748image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
08275774
98.1%
149637
 
0.6%
228855
 
0.3%
320413
 
0.2%
414708
 
0.2%
510576
 
0.1%
67797
 
0.1%
75951
 
0.1%
84156
 
< 0.1%
92919
 
< 0.1%
Other values (196)15301
 
0.2%
ValueCountFrequency (%)
08275774
98.1%
149637
 
0.6%
228855
 
0.3%
320413
 
0.2%
414708
 
0.2%
510576
 
0.1%
67797
 
0.1%
75951
 
0.1%
84156
 
< 0.1%
92919
 
< 0.1%
ValueCountFrequency (%)
5951
< 0.1%
4571
< 0.1%
4441
< 0.1%
4351
< 0.1%
4311
< 0.1%
4281
< 0.1%
4071
< 0.1%
3652
< 0.1%
3641
< 0.1%
3561
< 0.1%

supp_nn1
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct111
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04403084036
Minimum0
Maximum204
Zeros8394806
Zeros (%)99.5%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:21.507748image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum204
Range204
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9589073418
Coefficient of variation (CV)21.77808404
Kurtosis2559.564521
Mean0.04403084036
Median Absolute Deviation (MAD)0
Skewness39.37111543
Sum371448
Variance0.9195032901
MonotonicityNot monotonic
2022-03-29T13:21:21.618752image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
08394806
99.5%
16186
 
0.1%
24750
 
0.1%
33694
 
< 0.1%
43255
 
< 0.1%
53150
 
< 0.1%
62482
 
< 0.1%
72156
 
< 0.1%
81540
 
< 0.1%
91294
 
< 0.1%
Other values (101)12774
 
0.2%
ValueCountFrequency (%)
08394806
99.5%
16186
 
0.1%
24750
 
0.1%
33694
 
< 0.1%
43255
 
< 0.1%
53150
 
< 0.1%
62482
 
< 0.1%
72156
 
< 0.1%
81540
 
< 0.1%
91294
 
< 0.1%
ValueCountFrequency (%)
2041
< 0.1%
1701
< 0.1%
1531
< 0.1%
1461
< 0.1%
1401
< 0.1%
1331
< 0.1%
1312
< 0.1%
1252
< 0.1%
1241
< 0.1%
1181
< 0.1%

supp_nn2
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct110
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02059568613
Minimum0
Maximum231
Zeros8418641
Zeros (%)99.8%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:21.742753image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum231
Range231
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7254776633
Coefficient of variation (CV)35.22473875
Kurtosis7076.513323
Mean0.02059568613
Median Absolute Deviation (MAD)0
Skewness64.24186594
Sum173747
Variance0.52631784
MonotonicityNot monotonic
2022-03-29T13:21:21.866751image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
08418641
99.8%
13443
 
< 0.1%
22092
 
< 0.1%
31385
 
< 0.1%
41124
 
< 0.1%
5901
 
< 0.1%
6767
 
< 0.1%
7701
 
< 0.1%
8596
 
< 0.1%
9516
 
< 0.1%
Other values (100)5921
 
0.1%
ValueCountFrequency (%)
08418641
99.8%
13443
 
< 0.1%
22092
 
< 0.1%
31385
 
< 0.1%
41124
 
< 0.1%
5901
 
< 0.1%
6767
 
< 0.1%
7701
 
< 0.1%
8596
 
< 0.1%
9516
 
< 0.1%
ValueCountFrequency (%)
2311
< 0.1%
2151
< 0.1%
1611
< 0.1%
1591
< 0.1%
1421
< 0.1%
1241
< 0.1%
1222
< 0.1%
1171
< 0.1%
1152
< 0.1%
1092
< 0.1%

supp_nn3
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct119
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01401716222
Minimum0
Maximum338
Zeros8426871
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:21.987749image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum338
Range338
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7159967192
Coefficient of variation (CV)51.0800052
Kurtosis16670.39446
Mean0.01401716222
Median Absolute Deviation (MAD)0
Skewness95.89343888
Sum118250
Variance0.5126513019
MonotonicityNot monotonic
2022-03-29T13:21:22.269752image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
08426871
99.9%
11377
 
< 0.1%
2962
 
< 0.1%
3795
 
< 0.1%
4674
 
< 0.1%
5545
 
< 0.1%
6464
 
< 0.1%
7404
 
< 0.1%
8340
 
< 0.1%
9295
 
< 0.1%
Other values (109)3360
 
< 0.1%
ValueCountFrequency (%)
08426871
99.9%
11377
 
< 0.1%
2962
 
< 0.1%
3795
 
< 0.1%
4674
 
< 0.1%
5545
 
< 0.1%
6464
 
< 0.1%
7404
 
< 0.1%
8340
 
< 0.1%
9295
 
< 0.1%
ValueCountFrequency (%)
3381
< 0.1%
2411
< 0.1%
2381
< 0.1%
1901
< 0.1%
1551
< 0.1%
1382
< 0.1%
1312
< 0.1%
1232
< 0.1%
1211
< 0.1%
1182
< 0.1%

supp_rep
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct143
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01289638194
Minimum0
Maximum410
Zeros8421120
Zeros (%)99.8%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:22.384750image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum410
Range410
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6566987904
Coefficient of variation (CV)50.92116484
Kurtosis54648.287
Mean0.01289638194
Median Absolute Deviation (MAD)0
Skewness173.3399859
Sum108795
Variance0.4312533014
MonotonicityNot monotonic
2022-03-29T13:21:22.488753image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
08421120
99.8%
12953
 
< 0.1%
22606
 
< 0.1%
31949
 
< 0.1%
41429
 
< 0.1%
51002
 
< 0.1%
6800
 
< 0.1%
7622
 
< 0.1%
8457
 
< 0.1%
9375
 
< 0.1%
Other values (133)2774
 
< 0.1%
ValueCountFrequency (%)
08421120
99.8%
12953
 
< 0.1%
22606
 
< 0.1%
31949
 
< 0.1%
41429
 
< 0.1%
51002
 
< 0.1%
6800
 
< 0.1%
7622
 
< 0.1%
8457
 
< 0.1%
9375
 
< 0.1%
ValueCountFrequency (%)
4101
< 0.1%
2951
< 0.1%
2681
< 0.1%
2641
< 0.1%
2571
< 0.1%
2272
< 0.1%
2231
< 0.1%
2161
< 0.1%
2061
< 0.1%
1981
< 0.1%

ano_date
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct7684
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26373.88164
Minimum21319
Maximum29949
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:22.608753image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum21319
5-th percentile23584
Q125230
median26371
Q327583
95-th percentile29045
Maximum29949
Range8630
Interquartile range (IQR)2353

Descriptive statistics

Standard deviation1633.573075
Coefficient of variation (CV)0.06193904625
Kurtosis-0.6114696233
Mean26373.88164
Median Absolute Deviation (MAD)1174
Skewness-0.08444615131
Sum2.224923601 × 1011
Variance2668560.991
MonotonicityNot monotonic
2022-03-29T13:21:22.715752image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
263072246
 
< 0.1%
263202220
 
< 0.1%
262972201
 
< 0.1%
263022198
 
< 0.1%
263122196
 
< 0.1%
263152190
 
< 0.1%
258802186
 
< 0.1%
259102181
 
< 0.1%
259052179
 
< 0.1%
259372178
 
< 0.1%
Other values (7674)8414112
99.7%
ValueCountFrequency (%)
213191
< 0.1%
220101
< 0.1%
220191
< 0.1%
220861
< 0.1%
221161
< 0.1%
222171
< 0.1%
222461
< 0.1%
222481
< 0.1%
222511
< 0.1%
222521
< 0.1%
ValueCountFrequency (%)
299498
 
< 0.1%
299484
 
< 0.1%
299478
 
< 0.1%
2994612
< 0.1%
2994511
< 0.1%
299449
 
< 0.1%
2994314
< 0.1%
2994219
< 0.1%
2994119
< 0.1%
2994024
< 0.1%

anonyme
Categorical

HIGH CARDINALITY

Distinct3579198
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
SQDSE57BRCXQ4442E
 
1292
W172QW69PFF8RH2TE
 
1182
QF77B3CCFW7CFSWQE
 
1056
Y8MCWE3HWADFE1N5E
 
1051
U60231AT1TUTGSWCE
 
1019
Other values (3579193)
8430487 

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2194422 ?
Unique (%)26.0%

Sample

1st rowGZ90EST3Q2Q7JB1HE
2nd row72UTA1848751GJFYE
3rd row41CY72XBEQRC6B3PE
4th rowKJASY3HU2MXGDQ6XE
5th rowPP7G4R91P5ACURKWE

Common Values

ValueCountFrequency (%)
SQDSE57BRCXQ4442E1292
 
< 0.1%
W172QW69PFF8RH2TE1182
 
< 0.1%
QF77B3CCFW7CFSWQE1056
 
< 0.1%
Y8MCWE3HWADFE1N5E1051
 
< 0.1%
U60231AT1TUTGSWCE1019
 
< 0.1%
J5B3GPGW9YG66UJ8E1001
 
< 0.1%
0GETB3UAGBCZS1MBE953
 
< 0.1%
WZ3MZGM4Z2A2BYNZE894
 
< 0.1%
YGGM7PU0J55STPT7E866
 
< 0.1%
1UT18PASNHRNRRSME849
 
< 0.1%
Other values (3579188)8425924
99.9%

Length

2022-03-29T13:21:23.089748image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sqdse57brcxq4442e1292
 
< 0.1%
w172qw69pff8rh2te1182
 
< 0.1%
qf77b3ccfw7cfswqe1056
 
< 0.1%
y8mcwe3hwadfe1n5e1051
 
< 0.1%
u60231at1tutgswce1019
 
< 0.1%
j5b3gpgw9yg66uj8e1001
 
< 0.1%
0getb3uagbczs1mbe953
 
< 0.1%
wz3mzgm4z2a2bynze894
 
< 0.1%
yggm7pu0j55stpt7e866
 
< 0.1%
1ut18pasnhrnrrsme849
 
< 0.1%
Other values (3579188)8425924
99.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

nbActe
Real number (ℝ≥0)

HIGH CORRELATION
SKEWED
ZEROS

Distinct821
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.422384335
Minimum0
Maximum1511
Zeros2113252
Zeros (%)25.1%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:23.210747image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q34
95-th percentile10
Maximum1511
Range1511
Interquartile range (IQR)4

Descriptive statistics

Standard deviation12.2612606
Coefficient of variation (CV)3.582666178
Kurtosis1387.087335
Mean3.422384335
Median Absolute Deviation (MAD)2
Skewness28.03181974
Sum28871532
Variance150.3385116
MonotonicityNot monotonic
2022-03-29T13:21:23.313750image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
02113252
25.1%
11749412
20.7%
21576649
18.7%
3870640
10.3%
4651817
 
7.7%
5399418
 
4.7%
6266769
 
3.2%
7173670
 
2.1%
8122501
 
1.5%
983697
 
1.0%
Other values (811)428262
 
5.1%
ValueCountFrequency (%)
02113252
25.1%
11749412
20.7%
21576649
18.7%
3870640
10.3%
4651817
 
7.7%
5399418
 
4.7%
6266769
 
3.2%
7173670
 
2.1%
8122501
 
1.5%
983697
 
1.0%
ValueCountFrequency (%)
15111
< 0.1%
14781
< 0.1%
14261
< 0.1%
14211
< 0.1%
13981
< 0.1%
13611
< 0.1%
13421
< 0.1%
13171
< 0.1%
12561
< 0.1%
11961
< 0.1%

nbRum
Real number (ℝ≥0)

Distinct47
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.165296304
Minimum1
Maximum90
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:23.438748image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile2
Maximum90
Range89
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5253617791
Coefficient of variation (CV)0.4508396512
Kurtosis291.1856556
Mean1.165296304
Median Absolute Deviation (MAD)0
Skewness7.102122185
Sum9830541
Variance0.276004999
MonotonicityNot monotonic
2022-03-29T13:21:23.543748image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
17403706
87.8%
2778464
 
9.2%
3188628
 
2.2%
442566
 
0.5%
513706
 
0.2%
64672
 
0.1%
72181
 
< 0.1%
8889
 
< 0.1%
9509
 
< 0.1%
10265
 
< 0.1%
Other values (37)501
 
< 0.1%
ValueCountFrequency (%)
17403706
87.8%
2778464
 
9.2%
3188628
 
2.2%
442566
 
0.5%
513706
 
0.2%
64672
 
0.1%
72181
 
< 0.1%
8889
 
< 0.1%
9509
 
< 0.1%
10265
 
< 0.1%
ValueCountFrequency (%)
901
 
< 0.1%
761
 
< 0.1%
591
 
< 0.1%
481
 
< 0.1%
471
 
< 0.1%
462
< 0.1%
441
 
< 0.1%
411
 
< 0.1%
391
 
< 0.1%
383
< 0.1%

modeEntree
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
8
8165051 
7
 
202998
N
 
49623
6
 
16508
0
 
1907

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row8
2nd row8
3rd row8
4th row8
5th row8

Common Values

ValueCountFrequency (%)
88165051
96.8%
7202998
 
2.4%
N49623
 
0.6%
616508
 
0.2%
01907
 
< 0.1%

Length

2022-03-29T13:21:23.657807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-03-29T13:21:23.716807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
88165051
96.8%
7202998
 
2.4%
n49623
 
0.6%
616508
 
0.2%
01907
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

modeSortie
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size128.7 MiB

cmu
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing632275
Missing (%)7.5%
Memory size128.7 MiB

motif
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)< 0.1%
Missing7283520
Missing (%)86.3%
Infinite0
Infinite (%)0.0%
Mean1.410001327
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:24.208807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.216173942
Coefficient of variation (CV)0.8625338986
Kurtosis15.40300049
Mean1.410001327
Median Absolute Deviation (MAD)0
Skewness3.591512336
Sum1625121
Variance1.479079057
MonotonicityNot monotonic
2022-03-29T13:21:24.302807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
11011859
 
12.0%
4122252
 
1.4%
912307
 
0.1%
25235
 
0.1%
3775
 
< 0.1%
5138
 
< 0.1%
61
 
< 0.1%
(Missing)7283520
86.3%
ValueCountFrequency (%)
11011859
12.0%
25235
 
0.1%
3775
 
< 0.1%
4122252
 
1.4%
5138
 
< 0.1%
61
 
< 0.1%
912307
 
0.1%
ValueCountFrequency (%)
912307
 
0.1%
61
 
< 0.1%
5138
 
< 0.1%
4122252
 
1.4%
3775
 
< 0.1%
25235
 
0.1%
11011859
12.0%

dp
Categorical

HIGH CARDINALITY

Distinct11751
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Z491
 
480373
Z511
 
429172
Z5101
 
235762
Z512
 
211660
O800
 
154823
Other values (11746)
6924297 

Length

Max length6
Median length4
Mean length4.128800355
Min length3

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique830 ?
Unique (%)< 0.1%

Sample

1st rowR073
2nd rowR073
3rd rowR073
4th rowR073
5th rowR073

Common Values

ValueCountFrequency (%)
Z491480373
 
5.7%
Z511429172
 
5.1%
Z5101235762
 
2.8%
Z512211660
 
2.5%
O800154823
 
1.8%
Z098138942
 
1.6%
F10097801
 
1.2%
Z38094393
 
1.1%
O04988569
 
1.0%
Z50276764
 
0.9%
Other values (11741)6427828
76.2%

Length

2022-03-29T13:21:24.418807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
z491480373
 
5.7%
z511429172
 
5.1%
z5101235762
 
2.8%
z512211660
 
2.5%
o800154823
 
1.8%
z098138942
 
1.6%
f10097801
 
1.2%
z38094393
 
1.1%
o04988569
 
1.0%
z50276764
 
0.9%
Other values (11741)6427828
76.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

dr
Categorical

HIGH CARDINALITY
MISSING

Distinct7256
Distinct (%)0.4%
Missing6570678
Missing (%)77.9%
Memory size128.7 MiB
N185
432854 
C509
 
82712
C349
 
40896
C504
 
34768
G473
 
29936
Other values (7251)
1244243 

Length

Max length6
Median length4
Mean length4.027280344
Min length3

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1404 ?
Unique (%)0.1%

Sample

1st rowZ655
2nd rowG908
3rd rowC435
4th rowE1120
5th rowI255

Common Values

ValueCountFrequency (%)
N185432854
 
5.1%
C50982712
 
1.0%
C34940896
 
0.5%
C50434768
 
0.4%
G47329936
 
0.4%
C6128252
 
0.3%
C34125094
 
0.3%
C90023473
 
0.3%
F10222040
 
0.3%
C50820086
 
0.2%
Other values (7246)1125298
 
13.3%
(Missing)6570678
77.9%

Length

2022-03-29T13:21:24.525812image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
n185432854
 
23.2%
c50982712
 
4.4%
c34940896
 
2.2%
c50434768
 
1.9%
g47329936
 
1.6%
c6128252
 
1.5%
c34125094
 
1.3%
c90023473
 
1.3%
f10222040
 
1.2%
c50820086
 
1.1%
Other values (7246)1125298
60.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

cost
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct232122
Distinct (%)2.8%
Missing64
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2367.207365
Minimum89.00460458
Maximum923684.6284
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:24.636807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum89.00460458
5-th percentile318.7712886
Q1732.6216668
median1181.399914
Q32357.999696
95-th percentile7209.464619
Maximum923684.6284
Range923595.6238
Interquartile range (IQR)1625.378029

Descriptive statistics

Standard deviation5127.013157
Coefficient of variation (CV)2.165848769
Kurtosis967.3475729
Mean2367.207365
Median Absolute Deviation (MAD)557.819648
Skewness18.7949589
Sum1.996981577 × 1010
Variance26286263.91
MonotonicityNot monotonic
2022-03-29T13:21:24.745808image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
318.7712886466986
 
5.5%
1136.752379344799
 
4.1%
1929.859974194998
 
2.3%
634.4091606167357
 
2.0%
575.2234467121076
 
1.4%
172.7920649119437
 
1.4%
944.4049393111001
 
1.3%
757.996623887570
 
1.0%
668.018051973340
 
0.9%
176.656318372410
 
0.9%
Other values (232112)6677049
79.1%
ValueCountFrequency (%)
89.0046045829923
 
0.4%
153.357070628
 
< 0.1%
172.7920649119437
1.4%
176.49717684
 
< 0.1%
176.656318372410
0.9%
201.391135911710
 
0.1%
217.709536632
 
< 0.1%
217.979277956
 
< 0.1%
240.7719651
 
< 0.1%
276.3547941
 
< 0.1%
ValueCountFrequency (%)
923684.62841
< 0.1%
753882.2081
< 0.1%
752695.50831
< 0.1%
608113.64651
< 0.1%
604425.41491
< 0.1%
592103.76611
< 0.1%
591844.2961
< 0.1%
586288.01851
< 0.1%
577079.02111
< 0.1%
548877.41141
< 0.1%

raison
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
CMU
7311973 
AME
1002913 
SUV
 
121201

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCMU
2nd rowCMU
3rd rowCMU
4th rowCMU
5th rowCMU

Common Values

ValueCountFrequency (%)
CMU7311973
86.7%
AME1002913
 
11.9%
SUV121201
 
1.4%

Length

2022-03-29T13:21:24.852810image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-03-29T13:21:25.085807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
cmu7311973
86.7%
ame1002913
 
11.9%
suv121201
 
1.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

hp_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Sejour de plus d'une journée
5018610 
Hopital de jour
3417477 

Length

Max length28
Median length28
Mean length22.73367202
Min length15

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHopital de jour
2nd rowHopital de jour
3rd rowHopital de jour
4th rowSejour de plus d'une journée
5th rowHopital de jour

Common Values

ValueCountFrequency (%)
Sejour de plus d'une journée5018610
59.5%
Hopital de jour3417477
40.5%

Length

2022-03-29T13:21:25.164807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-03-29T13:21:25.225808image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
de8436087
23.9%
sejour5018610
14.2%
plus5018610
14.2%
d'une5018610
14.2%
journée5018610
14.2%
hopital3417477
9.7%
jour3417477
9.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

severity
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Pas de niveau de sévérité
5067343 
1
2116828 
2
712566 
3
 
387850
4
 
151500

Length

Max length25
Median length25
Mean length15.41618988
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPas de niveau de sévérité
2nd rowPas de niveau de sévérité
3rd rowPas de niveau de sévérité
4th rowPas de niveau de sévérité
5th rowPas de niveau de sévérité

Common Values

ValueCountFrequency (%)
Pas de niveau de sévérité5067343
60.1%
12116828
25.1%
2712566
 
8.4%
3387850
 
4.6%
4151500
 
1.8%

Length

2022-03-29T13:21:25.298807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-03-29T13:21:25.364807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
de10134686
35.3%
pas5067343
17.7%
niveau5067343
17.7%
sévérité5067343
17.7%
12116828
 
7.4%
2712566
 
2.5%
3387850
 
1.4%
4151500
 
0.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

ghm_racine
Categorical

HIGH CARDINALITY

Distinct614
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
28Z04
 
472898
28Z07
 
346199
28Z17
 
195174
14Z14
 
182910
20Z05
 
180588
Other values (609)
7058318 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05M13
2nd row05M13
3rd row05M13
4th row05M13
5th row05M13

Common Values

ValueCountFrequency (%)
28Z04472898
 
5.6%
28Z07346199
 
4.1%
28Z17195174
 
2.3%
14Z14182910
 
2.2%
20Z05180588
 
2.1%
20Z04144455
 
1.7%
23M20137546
 
1.6%
14Z08121855
 
1.4%
28Z18121361
 
1.4%
06M02120031
 
1.4%
Other values (604)6413070
76.0%

Length

2022-03-29T13:21:25.479809image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
28z04472898
 
5.6%
28z07346199
 
4.1%
28z17195174
 
2.3%
14z14182910
 
2.2%
20z05180588
 
2.1%
20z04144455
 
1.7%
23m20137546
 
1.6%
14z08121855
 
1.4%
28z18121361
 
1.4%
06m02120031
 
1.4%
Other values (604)6413070
76.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

cmd
Real number (ℝ≥0)

HIGH CORRELATION

Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.94639173
Minimum1
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:25.568808image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median11
Q320
95-th percentile28
Maximum28
Range27
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.812694859
Coefficient of variation (CV)0.6807066432
Kurtosis-1.060511126
Mean12.94639173
Median Absolute Deviation (MAD)6
Skewness0.4914453846
Sum109216887
Variance77.66359067
MonotonicityNot monotonic
2022-03-29T13:21:25.663807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
281328079
15.7%
6787148
 
9.3%
14740559
 
8.8%
4561921
 
6.7%
8544165
 
6.5%
1496573
 
5.9%
5451652
 
5.4%
3386992
 
4.6%
23379973
 
4.5%
20364846
 
4.3%
Other values (17)2394179
28.4%
ValueCountFrequency (%)
1496573
5.9%
2133915
 
1.6%
3386992
4.6%
4561921
6.7%
5451652
5.4%
6787148
9.3%
7227810
 
2.7%
8544165
6.5%
9290597
 
3.4%
10290150
 
3.4%
ValueCountFrequency (%)
281328079
15.7%
274474
 
0.1%
268509
 
0.1%
2514413
 
0.2%
23379973
 
4.5%
2214177
 
0.2%
21173266
 
2.1%
20364846
 
4.3%
19205108
 
2.4%
18102576
 
1.2%

departement
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct92
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
75
1024008 
59
 
551207
13
 
410296
974
 
365997
62
 
262776
Other values (87)
5821803 

Length

Max length3
Median length2
Mean length2.092951863
Min length2

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row59
2nd row59
3rd row59
4th row59
5th row59

Common Values

ValueCountFrequency (%)
751024008
 
12.1%
59551207
 
6.5%
13410296
 
4.9%
974365997
 
4.3%
62262776
 
3.1%
69250907
 
3.0%
973245537
 
2.9%
76235989
 
2.8%
33216617
 
2.6%
60211493
 
2.5%
Other values (82)4661260
55.3%

Length

2022-03-29T13:21:25.768807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
751024008
 
12.1%
59551207
 
6.5%
13410296
 
4.9%
974365997
 
4.3%
62262776
 
3.1%
69250907
 
3.0%
973245537
 
2.9%
76235989
 
2.8%
33216617
 
2.6%
60211493
 
2.5%
Other values (82)4661260
55.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

id_dep
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct92
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
75
1024008 
59
 
551207
13
 
410296
974
 
365997
62
 
262776
Other values (87)
5821803 

Length

Max length3
Median length2
Mean length2.092951863
Min length2

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row59
2nd row59
3rd row59
4th row59
5th row59

Common Values

ValueCountFrequency (%)
751024008
 
12.1%
59551207
 
6.5%
13410296
 
4.9%
974365997
 
4.3%
62262776
 
3.1%
69250907
 
3.0%
973245537
 
2.9%
76235989
 
2.8%
33216617
 
2.6%
60211493
 
2.5%
Other values (82)4661260
55.3%

Length

2022-03-29T13:21:25.871809image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
751024008
 
12.1%
59551207
 
6.5%
13410296
 
4.9%
974365997
 
4.3%
62262776
 
3.1%
69250907
 
3.0%
973245537
 
2.9%
76235989
 
2.8%
33216617
 
2.6%
60211493
 
2.5%
Other values (82)4661260
55.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

region_label
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
ÎLE-DE-FRANCE
1763844 
HAUTS-DE-FRANCE
1183164 
AUVERGNE-RHÔNE-ALPES
740684 
OCCITANIE
718462 
PROVENCE-ALPES-CÔTE D'AZUR
613889 
Other values (13)
3416044 

Length

Max length26
Median length13
Mean length14.44000732
Min length5

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHAUTS-DE-FRANCE
2nd rowHAUTS-DE-FRANCE
3rd rowHAUTS-DE-FRANCE
4th rowHAUTS-DE-FRANCE
5th rowHAUTS-DE-FRANCE

Common Values

ValueCountFrequency (%)
ÎLE-DE-FRANCE1763844
20.9%
HAUTS-DE-FRANCE1183164
14.0%
AUVERGNE-RHÔNE-ALPES740684
8.8%
OCCITANIE718462
8.5%
PROVENCE-ALPES-CÔTE D'AZUR613889
 
7.3%
GRAND EST579849
 
6.9%
NOUVELLE-AQUITAINE558488
 
6.6%
NORMANDIE409083
 
4.8%
LA RÉUNION365997
 
4.3%
BOURGOGNE-FRANCHE-COMTÉ332823
 
3.9%
Other values (8)1169804
13.9%

Length

2022-03-29T13:21:25.981808image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
île-de-france1763844
15.7%
hauts-de-france1183164
 
10.5%
auvergne-rhône-alpes740684
 
6.6%
occitanie718462
 
6.4%
la644109
 
5.7%
provence-alpes-côte613889
 
5.5%
d'azur613889
 
5.5%
grand579849
 
5.2%
est579849
 
5.2%
nouvelle-aquitaine558488
 
5.0%
Other values (13)3251373
28.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

population_region
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
12 395 148
1763844 
5 987 172
1183164 
8 153 233
740684 
6 053 548
718462 
5 131 187
613889 
Other values (13)
3416044 

Length

Max length10
Median length9
Mean length9.018564294
Min length7

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5 987 172
2nd row5 987 172
3rd row5 987 172
4th row5 987 172
5th row5 987 172

Common Values

ValueCountFrequency (%)
12 395 1481763844
20.9%
5 987 1721183164
14.0%
8 153 233740684
8.8%
6 053 548718462
8.5%
5 131 187613889
 
7.3%
5 542 094579849
 
6.9%
6 081 985558488
 
6.6%
3 307 286409083
 
4.8%
868 846365997
 
4.3%
2 785 393332823
 
3.9%
Other values (8)1169804
13.9%

Length

2022-03-29T13:21:26.091809image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
52376902
 
9.7%
121763844
 
7.2%
3951763844
 
7.2%
1481763844
 
7.2%
61276950
 
5.2%
9871183164
 
4.8%
1721183164
 
4.8%
3932546
 
3.8%
8740684
 
3.0%
153740684
 
3.0%
Other values (32)10779018
44.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Libellé GHM
Categorical

HIGH CARDINALITY

Distinct2071
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Hémodialyse, en séances
 
472898
Chimiothérapie pour tumeur, en séances
 
346199
Chimiothérapie pour affection non tumorale, en séances
 
195174
Ethylisme aigu, niveau 1
 
178104
Accouchements uniques par voie basse chez une multipare, sans complication significative
 
155348
Other values (2066)
7088364 

Length

Max length171
Median length62
Mean length62.99421888
Min length8

Characters and Unicode

Total characters5738093
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDouleurs thoraciques, très courte durée
2nd rowDouleurs thoraciques, très courte durée
3rd rowDouleurs thoraciques, très courte durée
4th rowDouleurs thoraciques, très courte durée
5th rowDouleurs thoraciques, très courte durée

Common Values

ValueCountFrequency (%)
Hémodialyse, en séances472898
 
5.6%
Chimiothérapie pour tumeur, en séances346199
 
4.1%
Chimiothérapie pour affection non tumorale, en séances195174
 
2.3%
Ethylisme aigu, niveau 1178104
 
2.1%
Accouchements uniques par voie basse chez une multipare, sans complication significative155348
 
1.8%
Interruptions volontaires de grossesse : séjours de moins de 3 jours121855
 
1.4%
Radiothérapie conformationnelle avec modulation d'intensité, en séances121361
 
1.4%
Endoscopie digestive diagnostique et anesthésie, en ambulatoire111020
 
1.3%
Autres symptômes et motifs de recours aux soins de la CMD 23, très courte durée88700
 
1.1%
Nouveau-nés de 3300g et âge gestationnel de 40 SA et assimilés (groupe nouveau-nés 1), sans problème significatif77604
 
0.9%
Other values (2061)6567824
77.9%

Length

2022-03-29T13:21:26.224807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
niveau3413912
 
4.5%
et3298569
 
4.3%
de2998476
 
3.9%
12231616
 
2.9%
en2180434
 
2.8%
âge1812011
 
2.4%
à1803172
 
2.4%
ans1666444
 
2.2%
durée1576722
 
2.1%
courte1576722
 
2.1%
Other values (860)53981813
70.5%

Most occurring characters

ValueCountFrequency (%)
5738093
100.0%

Most occurring categories

ValueCountFrequency (%)
Control5738093
100.0%

Most frequent character per category

Control
ValueCountFrequency (%)
5738093
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common5738093
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5738093
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5738093
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5738093
100.0%

racine
Categorical

HIGH CARDINALITY

Distinct614
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
28Z04
 
472898
28Z07
 
346199
28Z17
 
195174
14Z14
 
182910
20Z05
 
180588
Other values (609)
7058318 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row05M13
2nd row05M13
3rd row05M13
4th row05M13
5th row05M13

Common Values

ValueCountFrequency (%)
28Z04472898
 
5.6%
28Z07346199
 
4.1%
28Z17195174
 
2.3%
14Z14182910
 
2.2%
20Z05180588
 
2.1%
20Z04144455
 
1.7%
23M20137546
 
1.6%
14Z08121855
 
1.4%
28Z18121361
 
1.4%
06M02120031
 
1.4%
Other values (604)6413070
76.0%

Length

2022-03-29T13:21:26.345807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
28z04472898
 
5.6%
28z07346199
 
4.1%
28z17195174
 
2.3%
14z14182910
 
2.2%
20z05180588
 
2.1%
20z04144455
 
1.7%
23m20137546
 
1.6%
14z08121855
 
1.4%
28z18121361
 
1.4%
06m02120031
 
1.4%
Other values (604)6413070
76.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Libellé GHM Racine
Categorical

HIGH CARDINALITY

Distinct614
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Hémodialyse, en séances
 
472898
Chimiothérapie pour tumeur, en séances
 
346199
Chimiothérapie pour affection non tumorale, en séances
 
195174
Accouchements uniques par voie basse chez une multipare
 
182910
Ethylisme aigu
 
180588
Other values (609)
7058318 

Length

Max length149
Median length52
Mean length51.97054452
Min length7

Characters and Unicode

Total characters4209144
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDouleurs thoraciques
2nd rowDouleurs thoraciques
3rd rowDouleurs thoraciques
4th rowDouleurs thoraciques
5th rowDouleurs thoraciques

Common Values

ValueCountFrequency (%)
Hémodialyse, en séances472898
 
5.6%
Chimiothérapie pour tumeur, en séances346199
 
4.1%
Chimiothérapie pour affection non tumorale, en séances195174
 
2.3%
Accouchements uniques par voie basse chez une multipare182910
 
2.2%
Ethylisme aigu180588
 
2.1%
Ethylisme avec dépendance144455
 
1.7%
Autres symptômes et motifs de recours aux soins de la CMD 23137546
 
1.6%
Interruptions volontaires de grossesse : séjours de moins de 3 jours121855
 
1.4%
Radiothérapie conformationnelle avec modulation d'intensité, en séances121361
 
1.4%
Autres gastroentérites et maladies diverses du tube digestif, âge inférieur à 18 ans120031
 
1.4%
Other values (604)6413070
76.0%

Length

2022-03-29T13:21:26.458807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
et3252966
 
5.3%
de2998476
 
4.8%
âge1812011
 
2.9%
à1803172
 
2.9%
ans1666444
 
2.7%
en1626065
 
2.6%
autres1472404
 
2.4%
séances1313939
 
2.1%
pour1293425
 
2.1%
la1260297
 
2.0%
Other values (847)43376213
70.1%

Most occurring characters

ValueCountFrequency (%)
4209144
100.0%

Most occurring categories

ValueCountFrequency (%)
Control4209144
100.0%

Most frequent character per category

Control
ValueCountFrequency (%)
4209144
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common4209144
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4209144
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4209144
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4209144
100.0%

label_cmd
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Séances
1328079 
Affections du tube digestif
787148 
Grossesses pathologiques, accouchements et affections du post-partum
740559 
Affections de l'appareil respiratoire
561921 
Affections et traumatismes de l'appareil musculosquelettique et du tissu conjonctif
544165 
Other values (22)
4474215 

Length

Max length87
Median length40
Mean length45.19724844
Min length7

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAffections de l'appareil circulatoire
2nd rowAffections de l'appareil circulatoire
3rd rowAffections de l'appareil circulatoire
4th rowAffections de l'appareil circulatoire
5th rowAffections de l'appareil circulatoire

Common Values

ValueCountFrequency (%)
Séances1328079
15.7%
Affections du tube digestif787148
 
9.3%
Grossesses pathologiques, accouchements et affections du post-partum740559
 
8.8%
Affections de l'appareil respiratoire561921
 
6.7%
Affections et traumatismes de l'appareil musculosquelettique et du tissu conjonctif544165
 
6.5%
Affections du système nerveux496573
 
5.9%
Affections de l'appareil circulatoire451652
 
5.4%
Affections des oreilles, du nez, de la gorge, de la bouche et des dents386992
 
4.6%
Facteurs influant sur l'état de santé et autres motifs de recours aux services de santé379973
 
4.5%
Troubles mentaux organiques liés à l'absorption de drogues ou induits par celles-ci364846
 
4.3%
Other values (17)2394179
28.4%

Length

2022-03-29T13:21:26.582807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
affections5840666
 
11.3%
de4799351
 
9.3%
et4535719
 
8.8%
du3801889
 
7.4%
l'appareil1836564
 
3.6%
des1746010
 
3.4%
séances1328079
 
2.6%
la1211374
 
2.3%
tube787148
 
1.5%
digestif787148
 
1.5%
Other values (83)24949757
48.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

lib_dp
Categorical

HIGH CARDINALITY

Distinct11749
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Dialyse extra-corporelle
 
480373
Séance de chimiothérapie pour tumeur
 
429172
Séance d'irradiation
 
235762
Autres formes de chimiothérapie
 
211660
Accouchement (unique) spontané par présentation du sommet
 
154823
Other values (11744)
6924297 

Length

Max length218
Median length36
Mean length43.82611464
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique830 ?
Unique (%)< 0.1%

Sample

1st rowAutres douleurs thoraciques
2nd rowAutres douleurs thoraciques
3rd rowAutres douleurs thoraciques
4th rowAutres douleurs thoraciques
5th rowAutres douleurs thoraciques

Common Values

ValueCountFrequency (%)
Dialyse extra-corporelle480373
 
5.7%
Séance de chimiothérapie pour tumeur429172
 
5.1%
Séance d'irradiation235762
 
2.8%
Autres formes de chimiothérapie211660
 
2.5%
Accouchement (unique) spontané par présentation du sommet154823
 
1.8%
Examen de contrôle après d'autres traitements pour d'autres affections138942
 
1.6%
Troubles mentaux et du comportement liés à l'utilisation d'alcool : intoxication aiguë97801
 
1.2%
Enfant unique, né à l'hôpital94393
 
1.1%
Avortement médical complet ou sans précision, sans complication88569
 
1.0%
Sevrage d'alcool76764
 
0.9%
Other values (11739)6427828
76.2%

Length

2022-03-29T13:21:26.703807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de2838422
 
5.9%
et1737373
 
3.6%
sans1571863
 
3.2%
du1462382
 
3.0%
autres1051015
 
2.2%
précision974847
 
2.0%
à845554
 
1.7%
pour816006
 
1.7%
séance739589
 
1.5%
chimiothérapie686158
 
1.4%
Other values (5919)35685670
73.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

top1_lib_dp_patients_None
Categorical

HIGH CARDINALITY

Distinct731
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Dialyse extra-corporelle
 
479730
Séance de chimiothérapie pour tumeur
 
429018
Accouchement (unique) spontané par présentation du sommet
 
271696
Séance d'irradiation
 
235704
Examen de contrôle après d'autres traitements pour d'autres affections
 
214521
Other values (726)
6805418 

Length

Max length197
Median length36
Mean length42.50051653
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDouleur thoracique, sans précision
2nd rowDouleur thoracique, sans précision
3rd rowDouleur thoracique, sans précision
4th rowDouleur thoracique, sans précision
5th rowDouleur thoracique, sans précision

Common Values

ValueCountFrequency (%)
Dialyse extra-corporelle479730
 
5.7%
Séance de chimiothérapie pour tumeur429018
 
5.1%
Accouchement (unique) spontané par présentation du sommet271696
 
3.2%
Séance d'irradiation235704
 
2.8%
Examen de contrôle après d'autres traitements pour d'autres affections214521
 
2.5%
Autres formes de chimiothérapie211593
 
2.5%
Troubles mentaux et du comportement liés à l'utilisation d'alcool : intoxication aiguë180309
 
2.1%
Gastroentérites et colites d'origine infectieuse, autres et non précisées167336
 
2.0%
Sevrage d'alcool144455
 
1.7%
Enfant unique, né à l'hôpital126235
 
1.5%
Other values (721)5975490
70.8%

Length

2022-03-29T13:21:26.826807image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de2483310
 
5.3%
et1975501
 
4.2%
sans1672542
 
3.6%
du1312440
 
2.8%
précision1129285
 
2.4%
autres957488
 
2.0%
pour925786
 
2.0%
séance739881
 
1.6%
à721090
 
1.5%
chimiothérapie647033
 
1.4%
Other values (1330)34362598
73.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

top3_region_label_patients_None
Categorical

HIGH CARDINALITY

Distinct199
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Île-de-France Hauts-de-France Auvergne-Rhône-Alpes
1829033 
Île-de-France Hauts-de-France Occitanie
1443868 
Hauts-de-France Île-de-France Occitanie
1053326 
Île-de-France Hauts-de-France Provence-Alpes-Côte d'Azur
 
339225
Hauts-de-France Île-de-France Provence-Alpes-Côte d'Azur
 
290788
Other values (194)
3479847 

Length

Max length71
Median length44
Mean length45.36348629
Min length23

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHauts-de-France Occitanie Provence-Alpes-Côte d'Azur
2nd rowHauts-de-France Occitanie Provence-Alpes-Côte d'Azur
3rd rowHauts-de-France Occitanie Provence-Alpes-Côte d'Azur
4th rowHauts-de-France Occitanie Provence-Alpes-Côte d'Azur
5th rowHauts-de-France Occitanie Provence-Alpes-Côte d'Azur

Common Values

ValueCountFrequency (%)
Île-de-France Hauts-de-France Auvergne-Rhône-Alpes1829033
21.7%
Île-de-France Hauts-de-France Occitanie1443868
17.1%
Hauts-de-France Île-de-France Occitanie1053326
12.5%
Île-de-France Hauts-de-France Provence-Alpes-Côte d'Azur339225
 
4.0%
Hauts-de-France Île-de-France Provence-Alpes-Côte d'Azur290788
 
3.4%
Île-de-France Auvergne-Rhône-Alpes Hauts-de-France265497
 
3.1%
Hauts-de-France Île-de-France Auvergne-Rhône-Alpes256153
 
3.0%
Hauts-de-France Occitanie Île-de-France212633
 
2.5%
Île-de-France Auvergne-Rhône-Alpes Provence-Alpes-Côte d'Azur211956
 
2.5%
Île-de-France Occitanie Auvergne-Rhône-Alpes197009
 
2.3%
Other values (189)2336599
27.7%

Length

2022-03-29T13:21:26.947810image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
île-de-france7923779
29.0%
hauts-de-france7384151
27.0%
occitanie3780469
13.8%
auvergne-rhône-alpes3354319
12.3%
provence-alpes-côte1330098
 
4.9%
d'azur1330098
 
4.9%
guyane391859
 
1.4%
la362129
 
1.3%
nouvelle-aquitaine336063
 
1.2%
réunion327654
 
1.2%
Other values (12)822288
 
3.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

top1_lib_dp_patients_SUV
Categorical

HIGH CARDINALITY

Distinct991
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Dialyse extra-corporelle
 
479730
Séance de chimiothérapie pour tumeur
 
429147
Accouchement (unique) spontané par présentation du sommet
 
270572
Séance d'irradiation
 
235704
Autres formes de chimiothérapie
 
211593
Other values (986)
6809341 

Length

Max length197
Median length36
Mean length42.70022239
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDouleur thoracique, sans précision
2nd rowDouleur thoracique, sans précision
3rd rowDouleur thoracique, sans précision
4th rowDouleur thoracique, sans précision
5th rowDouleur thoracique, sans précision

Common Values

ValueCountFrequency (%)
Dialyse extra-corporelle479730
 
5.7%
Séance de chimiothérapie pour tumeur429147
 
5.1%
Accouchement (unique) spontané par présentation du sommet270572
 
3.2%
Séance d'irradiation235704
 
2.8%
Autres formes de chimiothérapie211593
 
2.5%
Examen de contrôle après d'autres traitements pour d'autres affections187759
 
2.2%
Gastroentérites et colites d'origine infectieuse, autres et non précisées180996
 
2.1%
Troubles mentaux et du comportement liés à l'utilisation d'alcool : intoxication aiguë179645
 
2.1%
Avortement médical complet ou sans précision, sans complication121855
 
1.4%
Enfant unique, né à l'hôpital112733
 
1.3%
Other values (981)6026353
71.4%

Length

2022-03-29T13:21:27.068817image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de2866211
 
6.1%
et1885005
 
4.0%
sans1654077
 
3.5%
du1423626
 
3.0%
précision999331
 
2.1%
autres887001
 
1.9%
à799168
 
1.7%
pour772654
 
1.6%
séance740010
 
1.6%
chimiothérapie664073
 
1.4%
Other values (1539)34527650
73.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

top3_region_label_patients_SUV
Categorical

HIGH CARDINALITY

Distinct640
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Île-de-France Auvergne-Rhône-Alpes Hauts-de-France
 
482184
Guyane Mayotte Île-de-France
 
409778
Guyane Île-de-France Guadeloupe
 
369371
Île-de-France Mayotte Auvergne-Rhône-Alpes
 
349472
Mayotte Guyane Hauts-de-France
 
343389
Other values (635)
6481893 

Length

Max length63
Median length36
Mean length36.993655
Min length6

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHauts-de-France Guyane Bourgogne-Franche-Comté
2nd rowHauts-de-France Guyane Bourgogne-Franche-Comté
3rd rowHauts-de-France Guyane Bourgogne-Franche-Comté
4th rowHauts-de-France Guyane Bourgogne-Franche-Comté
5th rowHauts-de-France Guyane Bourgogne-Franche-Comté

Common Values

ValueCountFrequency (%)
Île-de-France Auvergne-Rhône-Alpes Hauts-de-France482184
 
5.7%
Guyane Mayotte Île-de-France409778
 
4.9%
Guyane Île-de-France Guadeloupe369371
 
4.4%
Île-de-France Mayotte Auvergne-Rhône-Alpes349472
 
4.1%
Mayotte Guyane Hauts-de-France343389
 
4.1%
Île-de-France Guyane Hauts-de-France296414
 
3.5%
Hauts-de-France Guyane Île-de-France279834
 
3.3%
Guyane Hauts-de-France Île-de-France260741
 
3.1%
Hauts-de-France Île-de-France Guyane251274
 
3.0%
Île-de-France Hauts-de-France Guyane235651
 
2.8%
Other values (630)5157979
61.1%

Length

2022-03-29T13:21:27.194816image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
guyane5360276
20.3%
île-de-france5342425
20.2%
hauts-de-france4521216
17.1%
mayotte2888925
10.9%
auvergne-rhône-alpes1976804
 
7.5%
guadeloupe1204292
 
4.6%
nouvelle-aquitaine712057
 
2.7%
est683258
 
2.6%
grand683258
 
2.6%
bourgogne-franche-comté646326
 
2.4%
Other values (13)2374262
9.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

top1_lib_dp_patients_CMU
Categorical

HIGH CARDINALITY

Distinct743
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Dialyse extra-corporelle
 
479730
Séance de chimiothérapie pour tumeur
 
428899
Accouchement (unique) spontané par présentation du sommet
 
271696
Séance d'irradiation
 
235704
Examen de contrôle après d'autres traitements pour d'autres affections
 
214521
Other values (738)
6805537 

Length

Max length197
Median length36
Mean length42.30120552
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDouleur thoracique, sans précision
2nd rowDouleur thoracique, sans précision
3rd rowDouleur thoracique, sans précision
4th rowDouleur thoracique, sans précision
5th rowDouleur thoracique, sans précision

Common Values

ValueCountFrequency (%)
Dialyse extra-corporelle479730
 
5.7%
Séance de chimiothérapie pour tumeur428899
 
5.1%
Accouchement (unique) spontané par présentation du sommet271696
 
3.2%
Séance d'irradiation235704
 
2.8%
Examen de contrôle après d'autres traitements pour d'autres affections214521
 
2.5%
Autres formes de chimiothérapie211593
 
2.5%
Troubles mentaux et du comportement liés à l'utilisation d'alcool : intoxication aiguë180309
 
2.1%
Gastroentérites et colites d'origine infectieuse, autres et non précisées146185
 
1.7%
Sevrage d'alcool144455
 
1.7%
Enfant unique, né à l'hôpital126235
 
1.5%
Other values (733)5996760
71.1%

Length

2022-03-29T13:21:27.475816image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de2421450
 
5.2%
et1939035
 
4.2%
sans1679106
 
3.6%
du1335817
 
2.9%
précision1117032
 
2.4%
autres947992
 
2.0%
pour925667
 
2.0%
séance739762
 
1.6%
à728711
 
1.6%
chimiothérapie646914
 
1.4%
Other values (1339)34095236
73.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

top3_region_label_patients_CMU
Categorical

HIGH CARDINALITY

Distinct251
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Île-de-France Hauts-de-France Auvergne-Rhône-Alpes
1368785 
Hauts-de-France Île-de-France Occitanie
1059397 
Île-de-France Hauts-de-France Occitanie
1039226 
Île-de-France Hauts-de-France Nouvelle-Aquitaine
426419 
Hauts-de-France Occitanie Île-de-France
 
384113
Other values (246)
4158147 

Length

Max length71
Median length44
Mean length45.10898643
Min length23

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHauts-de-France Occitanie Provence-Alpes-Côte d'Azur
2nd rowHauts-de-France Occitanie Provence-Alpes-Côte d'Azur
3rd rowHauts-de-France Occitanie Provence-Alpes-Côte d'Azur
4th rowHauts-de-France Occitanie Provence-Alpes-Côte d'Azur
5th rowHauts-de-France Occitanie Provence-Alpes-Côte d'Azur

Common Values

ValueCountFrequency (%)
Île-de-France Hauts-de-France Auvergne-Rhône-Alpes1368785
16.2%
Hauts-de-France Île-de-France Occitanie1059397
 
12.6%
Île-de-France Hauts-de-France Occitanie1039226
 
12.3%
Île-de-France Hauts-de-France Nouvelle-Aquitaine426419
 
5.1%
Hauts-de-France Occitanie Île-de-France384113
 
4.6%
Hauts-de-France Île-de-France Auvergne-Rhône-Alpes353636
 
4.2%
Hauts-de-France Île-de-France Provence-Alpes-Côte d'Azur314003
 
3.7%
Île-de-France Auvergne-Rhône-Alpes Hauts-de-France285528
 
3.4%
Île-de-France Hauts-de-France Provence-Alpes-Côte d'Azur190977
 
2.3%
Hauts-de-France La Réunion Occitanie179116
 
2.1%
Other values (241)2834887
33.6%

Length

2022-03-29T13:21:27.595816image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
île-de-france7529224
27.3%
hauts-de-france7515033
27.3%
occitanie3946563
14.3%
auvergne-rhône-alpes2948692
 
10.7%
provence-alpes-côte1263007
 
4.6%
d'azur1263007
 
4.6%
nouvelle-aquitaine711050
 
2.6%
la636192
 
2.3%
réunion593326
 
2.2%
est277895
 
1.0%
Other values (11)887218
 
3.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

top1_lib_dp_patients_AME
Categorical

HIGH CARDINALITY

Distinct846
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Dialyse extra-corporelle
 
479730
Séance de chimiothérapie pour tumeur
 
429376
Accouchement (unique) spontané par présentation du sommet
 
271696
Séance d'irradiation
 
235704
Autres formes de chimiothérapie
 
211593
Other values (841)
6807988 

Length

Max length218
Median length36
Mean length42.74104582
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDouleur thoracique, sans précision
2nd rowDouleur thoracique, sans précision
3rd rowDouleur thoracique, sans précision
4th rowDouleur thoracique, sans précision
5th rowDouleur thoracique, sans précision

Common Values

ValueCountFrequency (%)
Dialyse extra-corporelle479730
 
5.7%
Séance de chimiothérapie pour tumeur429376
 
5.1%
Accouchement (unique) spontané par présentation du sommet271696
 
3.2%
Séance d'irradiation235704
 
2.8%
Autres formes de chimiothérapie211593
 
2.5%
Examen de contrôle après d'autres traitements pour d'autres affections208732
 
2.5%
Troubles mentaux et du comportement liés à l'utilisation d'alcool : intoxication aiguë180309
 
2.1%
Gastroentérites et colites d'origine infectieuse, autres et non précisées144029
 
1.7%
Avortement médical complet ou sans précision, sans complication121855
 
1.4%
Intoxication par benzodiazépines121241
 
1.4%
Other values (836)6031822
71.5%

Length

2022-03-29T13:21:27.710817image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de2700204
 
5.7%
et1911002
 
4.0%
sans1786141
 
3.8%
du1372155
 
2.9%
précision1211499
 
2.6%
autres943033
 
2.0%
pour906823
 
1.9%
séance740239
 
1.6%
à704915
 
1.5%
chimiothérapie648615
 
1.4%
Other values (1408)34489746
72.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

top3_region_label_patients_AME
Categorical

HIGH CARDINALITY

Distinct260
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
Île-de-France Auvergne-Rhône-Alpes Hauts-de-France
887769 
Île-de-France Auvergne-Rhône-Alpes Provence-Alpes-Côte d'Azur
827211 
Île-de-France Guyane Auvergne-Rhône-Alpes
737396 
Île-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes
628082 
Île-de-France Hauts-de-France Auvergne-Rhône-Alpes
559090 
Other values (255)
4796539 

Length

Max length71
Median length50
Mean length47.9872205
Min length6

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes
2nd rowÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes
3rd rowÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes
4th rowÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes
5th rowÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes

Common Values

ValueCountFrequency (%)
Île-de-France Auvergne-Rhône-Alpes Hauts-de-France887769
 
10.5%
Île-de-France Auvergne-Rhône-Alpes Provence-Alpes-Côte d'Azur827211
 
9.8%
Île-de-France Guyane Auvergne-Rhône-Alpes737396
 
8.7%
Île-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes628082
 
7.4%
Île-de-France Hauts-de-France Auvergne-Rhône-Alpes559090
 
6.6%
Île-de-France Hauts-de-France Occitanie483847
 
5.7%
Île-de-France Provence-Alpes-Côte d'Azur Hauts-de-France468723
 
5.6%
Île-de-France Guyane Provence-Alpes-Côte d'Azur439798
 
5.2%
Île-de-France Guyane Hauts-de-France432984
 
5.1%
Île-de-France Auvergne-Rhône-Alpes Occitanie339264
 
4.0%
Other values (250)2631923
31.2%

Length

2022-03-29T13:21:27.832817image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
île-de-france8415291
28.4%
auvergne-rhône-alpes4675299
15.8%
hauts-de-france3766696
12.7%
provence-alpes-côte3258988
 
11.0%
d'azur3258988
 
11.0%
guyane2283729
 
7.7%
occitanie1529458
 
5.2%
grand791237
 
2.7%
est791237
 
2.7%
nouvelle-aquitaine343105
 
1.2%
Other values (12)513560
 
1.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

top3_Libellé GHM_patients
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size128.7 MiB

region
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
ÎLE-DE-FRANCE
1763844 
HAUTS-DE-FRANCE
1183164 
AUVERGNE-RHÔNE-ALPES
740684 
OCCITANIE
718462 
PROVENCE-ALPES-CÔTE D'AZUR
613889 
Other values (13)
3416044 

Length

Max length26
Median length13
Mean length14.44000732
Min length5

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHAUTS-DE-FRANCE
2nd rowHAUTS-DE-FRANCE
3rd rowHAUTS-DE-FRANCE
4th rowHAUTS-DE-FRANCE
5th rowHAUTS-DE-FRANCE

Common Values

ValueCountFrequency (%)
ÎLE-DE-FRANCE1763844
20.9%
HAUTS-DE-FRANCE1183164
14.0%
AUVERGNE-RHÔNE-ALPES740684
8.8%
OCCITANIE718462
8.5%
PROVENCE-ALPES-CÔTE D'AZUR613889
 
7.3%
GRAND EST579849
 
6.9%
NOUVELLE-AQUITAINE558488
 
6.6%
NORMANDIE409083
 
4.8%
LA RÉUNION365997
 
4.3%
BOURGOGNE-FRANCHE-COMTÉ332823
 
3.9%
Other values (8)1169804
13.9%

Length

2022-03-29T13:21:27.948817image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
île-de-france1763844
15.7%
hauts-de-france1183164
 
10.5%
auvergne-rhône-alpes740684
 
6.6%
occitanie718462
 
6.4%
la644109
 
5.7%
provence-alpes-côte613889
 
5.5%
d'azur613889
 
5.5%
grand579849
 
5.2%
est579849
 
5.2%
nouvelle-aquitaine558488
 
5.0%
Other values (13)3251373
28.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

effectif_region_2020
Real number (ℝ≥0)

HIGH CORRELATION

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4678417.733
Minimum2176665
Maximum6009918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size128.7 MiB
2022-03-29T13:21:28.032816image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum2176665
5-th percentile2176665
Q12176665
median6008732
Q36009918
95-th percentile6009918
Maximum6009918
Range3833253
Interquartile range (IQR)3833253

Descriptive statistics

Standard deviation1822982.242
Coefficient of variation (CV)0.3896578599
Kurtosis-1.588064633
Mean4678417.733
Median Absolute Deviation (MAD)1186
Skewness-0.641025306
Sum3.946753902 × 1013
Variance3.323264253 × 1012
MonotonicityNot monotonic
2022-03-29T13:21:28.109816image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
21766652912895
34.5%
60099182658118
31.5%
6008783892001
 
10.6%
6004706740684
 
8.8%
6008732558488
 
6.6%
6008898409083
 
4.8%
6009854245351
 
2.9%
288563619467
 
0.2%
ValueCountFrequency (%)
21766652912895
34.5%
288563619467
 
0.2%
6004706740684
 
8.8%
6008732558488
 
6.6%
6008783892001
 
10.6%
6008898409083
 
4.8%
6009854245351
 
2.9%
60099182658118
31.5%
ValueCountFrequency (%)
60099182658118
31.5%
6009854245351
 
2.9%
6008898409083
 
4.8%
6008783892001
 
10.6%
6008732558488
 
6.6%
6004706740684
 
8.8%
288563619467
 
0.2%
21766652912895
34.5%

grp_cln
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct21
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size128.7 MiB
no match
5836113 
13
586330 
11
 
325043
1
 
235304
2
 
188241
Other values (16)
1265056 

Length

Max length8
Median length8
Mean length6.030028021
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowno match
2nd rowno match
3rd rowno match
4th rowno match
5th rowno match

Common Values

ValueCountFrequency (%)
no match5836113
69.2%
13586330
 
7.0%
11325043
 
3.9%
1235304
 
2.8%
2188241
 
2.2%
18166369
 
2.0%
7154173
 
1.8%
15152302
 
1.8%
8141484
 
1.7%
20135501
 
1.6%
Other values (11)515227
 
6.1%

Length

2022-03-29T13:21:28.213816image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
no5836113
40.9%
match5836113
40.9%
13586330
 
4.1%
11325043
 
2.3%
1235304
 
1.6%
2188241
 
1.3%
18166369
 
1.2%
7154173
 
1.1%
15152302
 
1.1%
8141484
 
1.0%
Other values (12)650728
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Interactions

2022-03-29T13:17:47.544066image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-03-29T13:03:09.073625image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-03-29T13:03:58.969633image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-03-29T13:04:47.183820image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-03-29T13:05:37.354093image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-03-29T13:06:22.274473image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-03-29T13:07:02.673853image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-03-29T13:07:43.630435image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-03-29T13:08:24.968199image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2022-03-29T13:09:05.625592image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
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Correlations

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Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-03-29T13:21:28.532817image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-03-29T13:21:28.745816image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-03-29T13:21:28.953826image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
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Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

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Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-03-29T13:20:18.413140image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
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The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

finessmoisanneesexeghm2GHSagedureesupp_reasupp_sisupp_stfsupp_srcsupp_nn1supp_nn2supp_nn3supp_repano_dateanonymenbActenbRummodeEntreemodeSortiecmumotifdpdrcostraisonhp_typeseverityghm_racinecmddepartementid_depregion_labelpopulation_regionLibellé GHMracineLibellé GHM Racinelabel_cmdlib_dptop1_lib_dp_patients_Nonetop3_region_label_patients_Nonetop1_lib_dp_patients_SUVtop3_region_label_patients_SUVtop1_lib_dp_patients_CMUtop3_region_label_patients_CMUtop1_lib_dp_patients_AMEtop3_region_label_patients_AMEtop3_Libellé GHM_patientsregioneffectif_region_2020grp_cln
059078141582012105M13T18155300000000025318GZ90EST3Q2Q7JB1HE31881.0NaNR073NaN784.317704CMUHopital de jourPas de niveau de sévérité05M13055959HAUTS-DE-FRANCE5 987 172Douleurs thoraciques, très courte durée05M13Douleurs thoraciquesAffections de l'appareil circulatoireAutres douleurs thoraciquesDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionHauts-de-France Guyane Bourgogne-Franche-ComtéDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes{'Douleurs thoraciques, très courte durée': '50277', 'Actes diagnostiques par voie vasculaire, niveau 1': '27213', 'Mise en place de certains accès vasculaires pour des affections de la CMD 05, séjours de moins de 2 jours': '16227'}HAUTS-DE-FRANCE2176665.0no match
159078141532012205M13T1815540000000002634972UTA1848751GJFYE31881.0NaNR073NaN784.317704CMUHopital de jourPas de niveau de sévérité05M13055959HAUTS-DE-FRANCE5 987 172Douleurs thoraciques, très courte durée05M13Douleurs thoraciquesAffections de l'appareil circulatoireAutres douleurs thoraciquesDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionHauts-de-France Guyane Bourgogne-Franche-ComtéDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes{'Douleurs thoraciques, très courte durée': '50277', 'Actes diagnostiques par voie vasculaire, niveau 1': '27213', 'Mise en place de certains accès vasculaires pour des affections de la CMD 05, séjours de moins de 2 jours': '16227'}HAUTS-DE-FRANCE2176665.0no match
259078141542012105M13T1815650000000002640141CY72XBEQRC6B3PE21881.0NaNR073NaN784.317704CMUHopital de jourPas de niveau de sévérité05M13055959HAUTS-DE-FRANCE5 987 172Douleurs thoraciques, très courte durée05M13Douleurs thoraciquesAffections de l'appareil circulatoireAutres douleurs thoraciquesDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionHauts-de-France Guyane Bourgogne-Franche-ComtéDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes{'Douleurs thoraciques, très courte durée': '50277', 'Actes diagnostiques par voie vasculaire, niveau 1': '27213', 'Mise en place de certains accès vasculaires pour des affections de la CMD 05, séjours de moins de 2 jours': '16227'}HAUTS-DE-FRANCE2176665.0no match
359078141532012105M13T18158910000000024758KJASY3HU2MXGDQ6XE21881.0NaNR073NaN784.317704CMUSejour de plus d'une journéePas de niveau de sévérité05M13055959HAUTS-DE-FRANCE5 987 172Douleurs thoraciques, très courte durée05M13Douleurs thoraciquesAffections de l'appareil circulatoireAutres douleurs thoraciquesDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionHauts-de-France Guyane Bourgogne-Franche-ComtéDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes{'Douleurs thoraciques, très courte durée': '50277', 'Actes diagnostiques par voie vasculaire, niveau 1': '27213', 'Mise en place de certains accès vasculaires pour des affections de la CMD 05, séjours de moins de 2 jours': '16227'}HAUTS-DE-FRANCE2176665.0no match
4590781415112012205M13T18152900000000024607PP7G4R91P5ACURKWE21881.0NaNR073NaN784.317704CMUHopital de jourPas de niveau de sévérité05M13055959HAUTS-DE-FRANCE5 987 172Douleurs thoraciques, très courte durée05M13Douleurs thoraciquesAffections de l'appareil circulatoireAutres douleurs thoraciquesDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionHauts-de-France Guyane Bourgogne-Franche-ComtéDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes{'Douleurs thoraciques, très courte durée': '50277', 'Actes diagnostiques par voie vasculaire, niveau 1': '27213', 'Mise en place de certains accès vasculaires pour des affections de la CMD 05, séjours de moins de 2 jours': '16227'}HAUTS-DE-FRANCE2176665.0no match
559078141512012105M13T181547100000000251130DE9462ACMEA8FP3E31881.0NaNR073NaN784.317704CMUSejour de plus d'une journéePas de niveau de sévérité05M13055959HAUTS-DE-FRANCE5 987 172Douleurs thoraciques, très courte durée05M13Douleurs thoraciquesAffections de l'appareil circulatoireAutres douleurs thoraciquesDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionHauts-de-France Guyane Bourgogne-Franche-ComtéDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes{'Douleurs thoraciques, très courte durée': '50277', 'Actes diagnostiques par voie vasculaire, niveau 1': '27213', 'Mise en place de certains accès vasculaires pour des affections de la CMD 05, séjours de moins de 2 jours': '16227'}HAUTS-DE-FRANCE2176665.0no match
659078141522012105M13T18154410000000023547Y0ESXDSZ7G64H5NXE31881.0NaNR073NaN784.317704CMUSejour de plus d'une journéePas de niveau de sévérité05M13055959HAUTS-DE-FRANCE5 987 172Douleurs thoraciques, très courte durée05M13Douleurs thoraciquesAffections de l'appareil circulatoireAutres douleurs thoraciquesDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionHauts-de-France Guyane Bourgogne-Franche-ComtéDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes{'Douleurs thoraciques, très courte durée': '50277', 'Actes diagnostiques par voie vasculaire, niveau 1': '27213', 'Mise en place de certains accès vasculaires pour des affections de la CMD 05, séjours de moins de 2 jours': '16227'}HAUTS-DE-FRANCE2176665.0no match
759078141582012105M13T18155900000000025322QBCFCCSM43EPC9F5E21881.0NaNR073NaN784.317704CMUHopital de jourPas de niveau de sévérité05M13055959HAUTS-DE-FRANCE5 987 172Douleurs thoraciques, très courte durée05M13Douleurs thoraciquesAffections de l'appareil circulatoireAutres douleurs thoraciquesDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionHauts-de-France Guyane Bourgogne-Franche-ComtéDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes{'Douleurs thoraciques, très courte durée': '50277', 'Actes diagnostiques par voie vasculaire, niveau 1': '27213', 'Mise en place de certains accès vasculaires pour des affections de la CMD 05, séjours de moins de 2 jours': '16227'}HAUTS-DE-FRANCE2176665.0no match
859078141572012105M13T1815560000000002410816X1BYNN179DSF0YE61881.0NaNR073NaN784.317704CMUHopital de jourPas de niveau de sévérité05M13055959HAUTS-DE-FRANCE5 987 172Douleurs thoraciques, très courte durée05M13Douleurs thoraciquesAffections de l'appareil circulatoireAutres douleurs thoraciquesDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionHauts-de-France Guyane Bourgogne-Franche-ComtéDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes{'Douleurs thoraciques, très courte durée': '50277', 'Actes diagnostiques par voie vasculaire, niveau 1': '27213', 'Mise en place de certains accès vasculaires pour des affections de la CMD 05, séjours de moins de 2 jours': '16227'}HAUTS-DE-FRANCE2176665.0no match
959078141562012105M13T18154200000000024865YU2Z1Q7QPW9MD8KRE21881.0NaNR073NaN784.317704CMUHopital de jourPas de niveau de sévérité05M13055959HAUTS-DE-FRANCE5 987 172Douleurs thoraciques, très courte durée05M13Douleurs thoraciquesAffections de l'appareil circulatoireAutres douleurs thoraciquesDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionHauts-de-France Guyane Bourgogne-Franche-ComtéDouleur thoracique, sans précisionHauts-de-France Occitanie Provence-Alpes-Côte d'AzurDouleur thoracique, sans précisionÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-Alpes{'Douleurs thoraciques, très courte durée': '50277', 'Actes diagnostiques par voie vasculaire, niveau 1': '27213', 'Mise en place de certains accès vasculaires pour des affections de la CMD 05, séjours de moins de 2 jours': '16227'}HAUTS-DE-FRANCE2176665.0no match

Last rows

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843607798050000352015228Z15Z961456000000000259344YPSU029SGZ2JAAWE11881.0NaNZ5180E104201.391136CMUHopital de jourPas de niveau de sévérité28Z1528976976MAYOTTE299 348Oxygénothérapie hyperbare, en séances28Z15Oxygénothérapie hyperbare, en séancesSéancesSéance d'oxygénothérapie hyperbareSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareMayotte Provence-Alpes-Côte d'Azur Hauts-de-FranceSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareProvence-Alpes-Côte d'Azur Hauts-de-France Occitanie{'Chimiothérapie pour affection non tumorale, en séances': '49789', 'Chimiothérapie pour tumeur, en séances': '37606', 'Transfusions, en séances': '10231'}MAYOTTE2176665.0no match
843607898050000342015228Z15Z961456000000000259284YPSU029SGZ2JAAWE11881.0NaNZ5180E104201.391136CMUHopital de jourPas de niveau de sévérité28Z1528976976MAYOTTE299 348Oxygénothérapie hyperbare, en séances28Z15Oxygénothérapie hyperbare, en séancesSéancesSéance d'oxygénothérapie hyperbareSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareMayotte Provence-Alpes-Côte d'Azur Hauts-de-FranceSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareProvence-Alpes-Côte d'Azur Hauts-de-France Occitanie{'Chimiothérapie pour affection non tumorale, en séances': '49789', 'Chimiothérapie pour tumeur, en séances': '37606', 'Transfusions, en séances': '10231'}MAYOTTE2176665.0no match
843607998050000342015228Z15Z961456000000000259124YPSU029SGZ2JAAWE11881.0NaNZ5180E104201.391136CMUHopital de jourPas de niveau de sévérité28Z1528976976MAYOTTE299 348Oxygénothérapie hyperbare, en séances28Z15Oxygénothérapie hyperbare, en séancesSéancesSéance d'oxygénothérapie hyperbareSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareMayotte Provence-Alpes-Côte d'Azur Hauts-de-FranceSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareProvence-Alpes-Côte d'Azur Hauts-de-France Occitanie{'Chimiothérapie pour affection non tumorale, en séances': '49789', 'Chimiothérapie pour tumeur, en séances': '37606', 'Transfusions, en séances': '10231'}MAYOTTE2176665.0no match
843608098050000312016128Z15Z96146800000000024208PCR21K8N0MFPEW7QE1188NaN4.0Z5180E105201.391136SUVHopital de jourPas de niveau de sévérité28Z1528976976MAYOTTE299 348Oxygénothérapie hyperbare, en séances28Z15Oxygénothérapie hyperbare, en séancesSéancesSéance d'oxygénothérapie hyperbareSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareMayotte Provence-Alpes-Côte d'Azur Hauts-de-FranceSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareProvence-Alpes-Côte d'Azur Hauts-de-France Occitanie{'Chimiothérapie pour affection non tumorale, en séances': '49789', 'Chimiothérapie pour tumeur, en séances': '37606', 'Transfusions, en séances': '10231'}MAYOTTE2176665.0no match
843608198050000322016228Z15Z96145000000000025411Y508BK2GCST3G5H3E1188NaN4.0Z5180M8798201.391136SUVHopital de jourPas de niveau de sévérité28Z1528976976MAYOTTE299 348Oxygénothérapie hyperbare, en séances28Z15Oxygénothérapie hyperbare, en séancesSéancesSéance d'oxygénothérapie hyperbareSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareMayotte Provence-Alpes-Côte d'Azur Hauts-de-FranceSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareProvence-Alpes-Côte d'Azur Hauts-de-France Occitanie{'Chimiothérapie pour affection non tumorale, en séances': '49789', 'Chimiothérapie pour tumeur, en séances': '37606', 'Transfusions, en séances': '10231'}MAYOTTE2176665.0no match
843608298050000322016128Z15Z96146800000000024225PCR21K8N0MFPEW7QE1188NaN4.0Z5180E105201.391136SUVHopital de jourPas de niveau de sévérité28Z1528976976MAYOTTE299 348Oxygénothérapie hyperbare, en séances28Z15Oxygénothérapie hyperbare, en séancesSéancesSéance d'oxygénothérapie hyperbareSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareMayotte Provence-Alpes-Côte d'Azur Hauts-de-FranceSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareProvence-Alpes-Côte d'Azur Hauts-de-France Occitanie{'Chimiothérapie pour affection non tumorale, en séances': '49789', 'Chimiothérapie pour tumeur, en séances': '37606', 'Transfusions, en séances': '10231'}MAYOTTE2176665.0no match
843608398050000322016228Z15Z96145000000000025416Y508BK2GCST3G5H3E1188NaN4.0Z5180M8798201.391136SUVHopital de jourPas de niveau de sévérité28Z1528976976MAYOTTE299 348Oxygénothérapie hyperbare, en séances28Z15Oxygénothérapie hyperbare, en séancesSéancesSéance d'oxygénothérapie hyperbareSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareMayotte Provence-Alpes-Côte d'Azur Hauts-de-FranceSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareProvence-Alpes-Côte d'Azur Hauts-de-France Occitanie{'Chimiothérapie pour affection non tumorale, en séances': '49789', 'Chimiothérapie pour tumeur, en séances': '37606', 'Transfusions, en séances': '10231'}MAYOTTE2176665.0no match
843608498050000312016228Z15Z96145000000000025395Y508BK2GCST3G5H3E1188NaN4.0Z5180M8798201.391136SUVHopital de jourPas de niveau de sévérité28Z1528976976MAYOTTE299 348Oxygénothérapie hyperbare, en séances28Z15Oxygénothérapie hyperbare, en séancesSéancesSéance d'oxygénothérapie hyperbareSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareMayotte Provence-Alpes-Côte d'Azur Hauts-de-FranceSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareProvence-Alpes-Côte d'Azur Hauts-de-France Occitanie{'Chimiothérapie pour affection non tumorale, en séances': '49789', 'Chimiothérapie pour tumeur, en séances': '37606', 'Transfusions, en séances': '10231'}MAYOTTE2176665.0no match
843608598050000332017228Z15Z9614100000000025823EFCE04MJD9N9FDMPE1188NaN4.0Z5180M8690201.391136SUVHopital de jourPas de niveau de sévérité28Z1528976976MAYOTTE299 348Oxygénothérapie hyperbare, en séances28Z15Oxygénothérapie hyperbare, en séancesSéancesSéance d'oxygénothérapie hyperbareSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareMayotte Provence-Alpes-Côte d'Azur Hauts-de-FranceSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareProvence-Alpes-Côte d'Azur Hauts-de-France Occitanie{'Chimiothérapie pour affection non tumorale, en séances': '49789', 'Chimiothérapie pour tumeur, en séances': '37606', 'Transfusions, en séances': '10231'}MAYOTTE2176665.0no match
843608698050000322017228Z15Z961437480000000024954C8K7C8JR85Y5HGAWE19188NaN4.0Z5180E11507576.032194SUVSejour de plus d'une journéePas de niveau de sévérité28Z1528976976MAYOTTE299 348Oxygénothérapie hyperbare, en séances28Z15Oxygénothérapie hyperbare, en séancesSéancesSéance d'oxygénothérapie hyperbareSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareMayotte Provence-Alpes-Côte d'Azur Hauts-de-FranceSéance d'oxygénothérapie hyperbareLa Réunion Provence-Alpes-Côte d'Azur OccitanieSéance d'oxygénothérapie hyperbareProvence-Alpes-Côte d'Azur Hauts-de-France Occitanie{'Chimiothérapie pour affection non tumorale, en séances': '49789', 'Chimiothérapie pour tumeur, en séances': '37606', 'Transfusions, en séances': '10231'}MAYOTTE2176665.0no match

Duplicate rows

Most frequently occurring

moisanneeghm2agedureesupp_reasupp_sisupp_stfsupp_srcsupp_nn1supp_nn2supp_nn3supp_repano_dateanonymenbActenbRummodeEntreemotifdpdrcostraisonhp_typeseverityghm_racinecmddepartementid_depregion_labelpopulation_regionLibellé GHMracineLibellé GHM Racinelabel_cmdlib_dptop1_lib_dp_patients_Nonetop3_region_label_patients_Nonetop1_lib_dp_patients_SUVtop3_region_label_patients_SUVtop1_lib_dp_patients_CMUtop3_region_label_patients_CMUtop1_lib_dp_patients_AMEtop3_region_label_patients_AMEregioneffectif_region_2020grp_cln# duplicates
01201528Z07Z7600000000024626E1AHN4Y952FS54GNE0181.0Z511C5091136.752379AMEHopital de jourPas de niveau de sévérité28Z07287575ÎLE-DE-FRANCE12 395 148Chimiothérapie pour tumeur, en séances28Z07Chimiothérapie pour tumeur, en séancesSéancesSéance de chimiothérapie pour tumeurSéance de chimiothérapie pour tumeurÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesSéance de chimiothérapie pour tumeurÎle-de-France Mayotte Auvergne-Rhône-AlpesSéance de chimiothérapie pour tumeurÎle-de-France Hauts-de-France Nouvelle-AquitaineSéance de chimiothérapie pour tumeurÎle-de-France Auvergne-Rhône-Alpes Provence-Alpes-Côte d'AzurÎLE-DE-FRANCE6009918.0132
11201728Z17Z3300000000025358MKUT4UAT3UWFM3ZPE0181.0Z512M3521929.859974AMEHopital de jourPas de niveau de sévérité28Z17287575ÎLE-DE-FRANCE12 395 148Chimiothérapie pour affection non tumorale, en\nséances28Z17Chimiothérapie pour affection non tumorale, en\nséancesSéancesAutres formes de chimiothérapieAutres formes de chimiothérapieÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesAutres formes de chimiothérapieGuyane Mayotte Île-de-FranceAutres formes de chimiothérapieÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesAutres formes de chimiothérapieÎle-de-France Guyane Auvergne-Rhône-AlpesÎLE-DE-FRANCE6009918.0132
21202004M22Z800000000028042ABBNUH6G70GUB57KE2181.0Z098E840748.001617AMEHopital de jourPas de niveau de sévérité04M22047575ÎLE-DE-FRANCE12 395 148Explorations et surveillance pour affections de\nl'appareil respiratoire04M22Explorations et surveillance pour affections de\nl'appareil respiratoireAffections de l'appareil respiratoireExamen de contrôle après d'autres traitements pour d'autres affectionsExamen de contrôle après d'autres traitements pour d'autres affectionsÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesExamen de contrôle après d'autres traitements pour d'autres affectionsÎle-de-France Guyane Provence-Alpes-Côte d'AzurExamen de contrôle après d'autres traitements pour d'autres affectionsÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesExamen de contrôle après d'autres traitements pour d'autres affectionsÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-AlpesÎLE-DE-FRANCE6009918.0no match2
31202028Z04Z4100000000027229XS0CR8CW0C1S0ZF9E1181.0Z491N185318.771289AMEHopital de jourPas de niveau de sévérité28Z0428973973GUYANE294 436Hémodialyse, en séances28Z04Hémodialyse, en séancesSéancesDialyse extra-corporelleDialyse extra-corporelleÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesDialyse extra-corporelleÎle-de-France Auvergne-Rhône-Alpes Hauts-de-FranceDialyse extra-corporelleÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesDialyse extra-corporelleÎle-de-France Auvergne-Rhône-Alpes Hauts-de-FranceGUYANE6009918.0no match2
41202028Z04Z4100000000027243XS0CR8CW0C1S0ZF9E1181.0Z491N185318.771289AMEHopital de jourPas de niveau de sévérité28Z0428973973GUYANE294 436Hémodialyse, en séances28Z04Hémodialyse, en séancesSéancesDialyse extra-corporelleDialyse extra-corporelleÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesDialyse extra-corporelleÎle-de-France Auvergne-Rhône-Alpes Hauts-de-FranceDialyse extra-corporelleÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesDialyse extra-corporelleÎle-de-France Auvergne-Rhône-Alpes Hauts-de-FranceGUYANE6009918.0no match2
51202028Z04Z4100000000027248XS0CR8CW0C1S0ZF9E1181.0Z491N185318.771289AMEHopital de jourPas de niveau de sévérité28Z0428973973GUYANE294 436Hémodialyse, en séances28Z04Hémodialyse, en séancesSéancesDialyse extra-corporelleDialyse extra-corporelleÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesDialyse extra-corporelleÎle-de-France Auvergne-Rhône-Alpes Hauts-de-FranceDialyse extra-corporelleÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesDialyse extra-corporelleÎle-de-France Auvergne-Rhône-Alpes Hauts-de-FranceGUYANE6009918.0no match2
61202128Z04Z640000000002643192BBRHAB7NZWHB5SE1181.0Z491N185318.771289AMEHopital de jourPas de niveau de sévérité28Z0428973973GUYANE294 436Hémodialyse, en séances28Z04Hémodialyse, en séancesSéancesDialyse extra-corporelleDialyse extra-corporelleÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesDialyse extra-corporelleÎle-de-France Auvergne-Rhône-Alpes Hauts-de-FranceDialyse extra-corporelleÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesDialyse extra-corporelleÎle-de-France Auvergne-Rhône-Alpes Hauts-de-FranceGUYANE6009918.0no match2
71202128Z14Z3900000000027187EQE9D6SH772MB0B2E0181.0Z5130D630910.283735AMEHopital de jourPas de niveau de sévérité28Z14287575ÎLE-DE-FRANCE12 395 148Transfusions, en séances28Z14Transfusions, en séancesSéancesSéance de transfusion de produit sanguin labileSéance de transfusion de produit sanguin labileÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesSéance de transfusion de produit sanguin labileMayotte Île-de-France Auvergne-Rhône-AlpesSéance de transfusion de produit sanguin labileÎle-de-France Hauts-de-France Auvergne-Rhône-AlpesSéance de transfusion de produit sanguin labileÎle-de-France Auvergne-Rhône-Alpes Provence-Alpes-Côte d'AzurÎLE-DE-FRANCE6009918.0no match2
82201328Z24Z5400000000023523R1WXSJHPZTBR0PWPE1181.0Z5101C50989.004605AMEHopital de jourPas de niveau de sévérité28Z24287676NORMANDIE3 307 286Techniques complexes d'irradiation externe sans\nrepositionnement, en séances28Z24Techniques complexes d'irradiation externe sans\nrepositionnement, en séancesSéancesSéance d'irradiationSéance d'irradiationÎle-de-France Auvergne-Rhône-Alpes Grand EstSéance d'irradiationGuadeloupe Île-de-France Auvergne-Rhône-AlpesSéance d'irradiationAuvergne-Rhône-Alpes Île-de-France Grand EstSéance d'irradiationÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-AlpesNORMANDIE6008898.0no match2
92201328Z24Z5400000000023530R1WXSJHPZTBR0PWPE1181.0Z5101C50989.004605AMEHopital de jourPas de niveau de sévérité28Z24287676NORMANDIE3 307 286Techniques complexes d'irradiation externe sans\nrepositionnement, en séances28Z24Techniques complexes d'irradiation externe sans\nrepositionnement, en séancesSéancesSéance d'irradiationSéance d'irradiationÎle-de-France Auvergne-Rhône-Alpes Grand EstSéance d'irradiationGuadeloupe Île-de-France Auvergne-Rhône-AlpesSéance d'irradiationAuvergne-Rhône-Alpes Île-de-France Grand EstSéance d'irradiationÎle-de-France Provence-Alpes-Côte d'Azur Auvergne-Rhône-AlpesNORMANDIE6008898.0no match2